This guidebook explains how data teams can avoid being paralyzed by uncertainty in how to navigate increasing data regulations.get the white paper
Data governance is obviously not a new concept — as long as data has been collected and stored, companies have needed some level of policy and oversight for its management. However, the age of AI has ushered in data democratization, self-serve analytics, and rapid model deployment at a scale that present both more and different risks.
For those in risk management roles, unfortunately, the process of model risk validation has not scaled as quickly as the building of models themselves. One of the advantages that data science, machine learning, and AI platforms bring is the ability to centralize data effort, allowing for model risk validation and processes to scale as well.